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  1. International Journal of Multimedia Information Retrieval
  2. International Journal of Multimedia Information Retrieval : Volume 4
  3. International Journal of Multimedia Information Retrieval : Volume 4, Issue 4, December 2015
  4. Region-based image retrieval using shape-adaptive DCT
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International Journal of Multimedia Information Retrieval : Volume 6
International Journal of Multimedia Information Retrieval : Volume 5
International Journal of Multimedia Information Retrieval : Volume 4
International Journal of Multimedia Information Retrieval : Volume 4, Issue 4, December 2015
aMM: Towards adaptive ranking of multi-modal documents
Bregman pooling: feature-space local pooling for image classification
Region-based image retrieval using shape-adaptive DCT
Erratum to: Region-based image retrieval using shape-adaptive DCT
Studying the impact of sequence clustering on near-duplicate video retrieval: an experimental comparison
Detection of social events in streams of social multimedia
International Journal of Multimedia Information Retrieval : Volume 4, Issue 3, September 2015
International Journal of Multimedia Information Retrieval : Volume 4, Issue 2, June 2015
International Journal of Multimedia Information Retrieval : Volume 4, Issue 1, March 2015
International Journal of Multimedia Information Retrieval : Volume 3
International Journal of Multimedia Information Retrieval : Volume 2
International Journal of Multimedia Information Retrieval : Volume 1

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Region-based image retrieval using shape-adaptive DCT

Content Provider Springer Nature Link
Author Belloulata, Kamel Kpalma, Kidiyo Belalia, Amina
Copyright Year 2015
Abstract Content-based image retrieval (CBIR) is the process of searching digital images in a large database based on features, such as color, texture and shape of a given query image. As many images are compressed by transforms, constructing the feature vector directly in transform domain is a very popular topic. Therefore, features can be extracted directly from images in compressed format by using, for example, discrete cosine transform (DCT) for JPEG compressed images. Also, region-based image retrieval (RBIR) has attracted great interest in recent years. This paper proposes a new RBIR approach using shape-adaptive discrete cosine transform (SA-DCT). In this retrieval system, an image has a prior segmentation alpha plane, which is defined exactly as in MPEG-4. Therefore, an image is represented by segmented regions, each of which is associated with a feature vector derived from DCT and SA-DCT coefficients. Users can select any region as the main theme of the query image. The similarity between a query image and any database image is ranked according to a same similarity measure computed from the selected regions between two images. For those images without distinctive objects and scenes, users can still select the whole image as the query condition. The experimental results show that the proposed approach is able to identify main objects and reduce the influence of background in the image, and thus improve the performance of image retrieval in comparison with a conventional CBIR based on DCT.
Starting Page 261
Ending Page 276
Page Count 16
File Format PDF
ISSN 21926611
Journal International Journal of Multimedia Information Retrieval
Volume Number 4
Issue Number 4
e-ISSN 2192662X
Language English
Publisher Springer London
Publisher Date 2015-08-25
Publisher Place London
Access Restriction One Nation One Subscription (ONOS)
Subject Keyword Region-based image retrieval (RBIR) Content-based image retrieval (CBIR) DCT Segmentation Semantic image retrieval Information Storage and Retrieval Data Mining and Knowledge Discovery Image Processing and Computer Vision Computer Science Information Systems Applications (incl. Internet) Multimedia Information Systems SA-DCT
Content Type Text
Resource Type Article
Subject Library and Information Sciences Information Systems Media Technology
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